I was working on comparing and finding which models are better to predict the data and venturing into non linear modelling, I was trying out various combinations and seeing which was the best fit across the models.
First up trying to model diabetes as just a factor of obesity, and then it’s subsequent powers of 2,3,4,5.
This will also be done to a log of obesity, and a log of the obesity and diabetes both.
I will use all the above to compare the fits by P values and see which one is turning out best.
I will also further be carrying out tests for Inactivity data the same way but while writing this I realised that it contains some states with no data for inactivity hence making it difficult to run the poly function.
But for now focusing on trying to fit on the basis of transformations to obesity,
As you can see from the P values of the compared models, you can see that the most appropriate fit would be achieved by using the quadratic model rather than any higher ones, however it is interesting to notice that the log model and the 5th power non linear fit are similar in P value.
Will continue with more tests and see how the fits are turning out.